Single camera head tracking systems occasionally “lose track” of the subject (whose head the system is tracking) as the subject moves and/or the viewed scene changes. For instance, the subject may turn from the camera thereby causing the back of the subject's head to face the camera. Because the back of the head, as compared to the face, includes relatively few detectable features, the system may not be able to identify the head well enough to track the head. Moreover, at times the subject might move behind or otherwise become occluded by some object. Again, as a result, the system can lose track of the head. The system may also drift from accurately detecting the subject's head (and its position, pose, etc.) due to accumulated error within an algorithm estimating the position of the head (and/or for other reasons). Indeed, at some point, the detected position of the head might differ sufficiently from the actual position of the head that the system begins focusing on (or otherwise operating upon) other aspects of the scene. Moreover, this result might occur even when the subject remains stationary.
Multi-camera systems partially alleviate some of the challenges associated with these single-camera systems. However, these multi-camera systems carry with them certain complexities which offset many of their advantages. For instance, while multi-camera systems possess better overall abilities to perform head tracking, these multi-camera systems require accurate knowledge of the geometry between the cameras (i.e., the relative positions and the relative orientations of the cameras). Obtaining that information can be difficult and time consuming, particularly when the multi-camera system views a large area.
As difficult as obtaining information regarding the camera related geometry may be, maintaining that information poses perhaps even greater challenges. For instance, the user might intentionally move one or more of the cameras. In which case, the user may have to recalibrate the tracking algorithms which relate information obtained by one camera to information obtained from the other cameras. In addition, or in the alternative, the user might unintentionally move one of the cameras or some other event (for instance, malicious tampering with the system) might cause the camera related geometry to change. No matter the cause of the change, the user must re-calibrate the system to eliminate the errors, malfunctions, etc. associated with the change to the camera related geometry.